Samsung Galaxy S23
Geekbench ML Score
964
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 05 2024 12:27 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911B |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 6.89 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
433
81.0 IPS |
|
|
Image Classification (F16)
|
100% |
469
87.7 IPS |
|
|
Image Classification (I8)
|
97% |
782
146.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
618
10.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
615
10.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
765
12.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1112
1.35 IPS |
|
|
Pose Estimation (F16)
|
100% |
1069
1.29 IPS |
|
|
Pose Estimation (I8)
|
100% |
4329
5.24 IPS |
|
|
Object Detection (F32)
|
100% |
469
35.0 IPS |
|
|
Object Detection (F16)
|
100% |
499
37.3 IPS |
|
|
Object Detection (I8)
|
61% |
1123
83.8 IPS |
|
|
Face Detection (F32)
|
100% |
1069
12.7 IPS |
|
|
Face Detection (F16)
|
100% |
1017
12.1 IPS |
|
|
Face Detection (I8)
|
86% |
1716
20.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1110
8.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
1043
8.09 IPS |
|
|
Depth Estimation (I8)
|
95% |
2089
16.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1873
2.46 IPS |
|
|
Style Transfer (F16)
|
100% |
1888
2.48 IPS |
|
|
Style Transfer (I8)
|
98% |
4372
5.75 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
696
24.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
703
25.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2056
73.4 IPS |
|
|
Text Classification (F32)
|
100% |
573
823.0 IPS |
|
|
Text Classification (F16)
|
100% |
586
842.0 IPS |
|
|
Text Classification (I8)
|
92% |
453
650.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1058
19.5 IPS |
|
|
Machine Translation (F16)
|
100% |
969
17.8 IPS |
|
|
Machine Translation (I8)
|
64% |
490
9.02 IPS |
